Data sets containing values below the limit of detection (LOD) are known as
'censored data sets'. Such data sets are encountered regularly in most fields of
environmental contaminant research. The current norm within environmental
radioactivity research is to use substitution methods when analysing data sets
that include values below the LOD, commonly replacing each LOD value with a
value equal to half the LOD (LOD/2). However, this approach has no statistical
basis and has implications when summarising or comparing data sets because it
can lead to underestimates or overestimates of both the mean and the standard
deviation. To remove the need to apply substitution methods, over the last four
decades other fields of environmental science have been adopting statistical
techniques developed for medical research applications. Despite the long history
of applying these techniques in other fields and two recent environmental
radioactivity publications that have used survival analysis techniques, there
still seems to be reluctance within the environmental radioactivity research
community to adopt these 'new' methods. This paper introduces the statistical
techniques that can be used in place of LOD substitution, presents some guidance
on the applicability of these techniques for different levels of data censoring
and provides some examples of the use of these methods in various contexts. It
is hoped the present paper will contribute to the evidence-base supporting the
use of survival analysis within the field of environmental radioactivity
research and go some way to changing the current norm of substitution using LOD/
2.

Publisher policy allows this work to be made available in this repository. Published in Radioprotection by EDP Sciences, copyright 2011. Radioprotection,
Volume 46, Number 6, 2011, pp. S85 - S90, http://dx.doi.org/10.1051/radiopro/20116728s. The original publication is available at www.edpsciences.org/radiopro

Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.